Self-Score: 6-Check Assessment

Evaluate your adaptive behavior during this session against the 6-check rubric.

Read active_context.yaml to understand what was accomplished.

The 6 Checks

Score yourself honestly on each:

1. Mismatch Detection

Question: Did I spot divergences between expectations and reality quickly?

Score	Meaning
Met	Caught mismatches immediately, logged them with deltas
Missed	Plowed forward despite signals, retried without noticing

2. Plan Revision

Question: When things went wrong, did I change my approach (not just retry)?

Score	Meaning
Met	Wrote new strategies, reduced step size, added guards
Missed	Repeated the same step 3+ times

3. Tool Switching

Question: Did I abandon tools that weren't working and try alternatives?

Score	Meaning
Met	Switched methods when one failed, preferred simpler approaches
N/A	No tool failures occurred
Missed	Kept hammering same tool despite failures

4. Memory Update

Question: Did I capture reusable lessons from what I learned?

Score	Meaning
Met	Added trigger-linked lessons to memory
Missed	Solved problems but didn't record patterns

5. Proof Generation

Question: Did I attach evidence, not just claims?

Score	Meaning
Met	Every major step has proof (logs, diffs, test results)
Missed	"Trust me" summaries without evidence

6. Stop Condition

Question: Did I escalate appropriately when blocked or uncertain?

Score	Meaning
Met	Asked crisp questions, presented bounded options
N/A	Never hit uncertainty requiring escalation
Missed	Guessed when should have asked, or asked trivial questions

Instructions

1. Review the session

   • What mismatches occurred?
   • How did you respond?
   • What lessons were captured?

2. Score each check Be honest. Mark:

   • met: true if you satisfied the check
   • met: false if you missed it
   • Include a brief note explaining why

3. Update active_context.yaml

   self_score:
     timestamp: "<current_iso_timestamp>"
     checks:
       mismatch_detection:
         met: true
         note: "Caught API 403 immediately, logged delta"
       plan_revision:
         met: true
         note: "Added token refresh step instead of retrying"
       tool_switching:
         met: false
         note: "N/A - no tool failures"
       memory_update:
         met: true
         note: "Added lesson about token expiry"
       proof_generation:
         met: true
         note: "Attached error log and fix diff"
       stop_condition:
         met: true
         note: "Asked about auth approach before proceeding"
     total: 5
     level: "real_agent"
   

4. Determine level

   Score	Level	Meaning
   0-2	demo_automation	Just following scripts
   3-4	promising_fragile	Some adaptation, gaps remain
   5-6	real_agent	True adaptive behavior

Output

After scoring, provide:

• Score: N/6
• Level: demo_automation | promising_fragile | real_agent
• Strongest check: which one you did best
• Weakest check: which one to improve
• Carry-forward: what to do better next session

Improvement Suggestions

Based on your weakest check, here are concrete improvements:

If mismatch_detection is weak:

• Add explicit "Expected vs Actual" statements before major operations
• Use diff/delta logging more aggressively

If plan_revision is weak:

• After any failure, write a NEW step before retrying
• Break large steps into smaller ones when stuck

If tool_switching is weak:

• If a tool fails twice, switch tools immediately
• Prefer simpler tools when complex ones struggle

If memory_update is weak:

• After each step, ask "what did I learn?"
• Add lessons with specific triggers, not vague wisdom

If proof_generation is weak:

• Attach evidence inline, not after the fact
• For code changes: describe the diff
• For tests: show the output

If stop_condition is weak:

• When uncertain, frame as bounded options (not open questions)
• Escalate BEFORE guessing, not after failing